code: def _process_op_recipe(op, p_idx, order):
      """Process an existing recipe of an operation."""
      recipe = op.grad_recipe[p_idx]
      if recipe is None:
          return None
  
      recipe = qml.math.array(recipe)
      if order == 1:
          return process_shifts(recipe, batch_duplicates=False)
  
      # Try to obtain the period of the operator frequencies for iteration of custom recipe
      try:
          period = frequencies_to_period(
              op.parameter_frequencies[p_idx]
          )
      except qml.operation.ParameterFrequenciesUndefinedError:
          period = None
  
      # Iterate the custom recipe to obtain the second-order recipe
      if qml.math.allclose(
          recipe[:, 1], qml.math.ones_like(recipe[:, 1])
      ):
          # If the multipliers are ones, we do not include them in the iteration
          # but keep track of them manually
          iter_c, iter_s = process_shifts(
              _iterate_shift_rule(recipe[:, ::2], order, period)
          ).T
          return qml.math.stack(
              [iter_c, qml.math.ones_like(iter_c), iter_s]
          ).T
  
      return process_shifts(_iterate_shift_rule(recipe, order, period))
  
imports: from typing import Sequence, Callable
  from functools import partial
  import numpy
  import pennylane
  from pennylane.measurements import VarianceMP
  from pennylane import transform
  from pennylane.transforms.tape_expand import expand_invalid_trainable
  from pennylane.gradients.gradient_transform import _contract_qjac_with_cjac
  from .finite_difference import finite_diff
  from .general_shift_rules import _iterate_shift_rule, frequencies_to_period, generate_shifted_tapes, process_shifts
  from .gradient_transform import _all_zero_grad, assert_no_state_returns, assert_no_tape_batching, assert_multimeasure_not_broadcasted, choose_trainable_params, find_and_validate_gradient_methods, _no_trainable_grad, reorder_grads
label_desc: Use image node_id 2 for calling a global function with example usage: _process_op_recipe(op, p_idx, order) and returns: process_shifts, None, process_shifts, qml